Description: This people provides a derivation of continuous and curtate inequalities of life contingent functions and shows how the proofs of the continuous inequalities are of an entirely different nature from the usual proofs for the curtate inequalities Followed by discussion papers submitted by several authors

Description: Recent articles addressed the subject of fuzzy regression [FR] and the term structure of interest rates [TSIR]. Their approach relied on possibilistic regression. Although possibilistic regression has been used in many applications, it has a number of limitations, not the least of which is its nebulous relation to the least-squares concept. As an alternative to possibilistic regression, this paper uses fuzzy least square regression to investigate the TSIR.

Description: A key concept in post-retirement planning is the random variable future lifetime of a life aged x. While age is an important factor in the determination of this variable, there are other relevant factors, like the state of health and the character of a life aged x. The purpose of this article is to presents some preliminary observations regarding the conceptualization of future lifetime as a fuzzy random variable.

Description: This paper examines four and-a-half years of prescription records for an elderly population who have relatively comprehensive out-of-hospital drug coverage under the Pharmaceutical Assistance Contract for the Elderly program in Pennsylvania. The result is a discussion of the determination of non-parametric estimations of the distributions. From Actuarial Research Clearing House 1991, Vol 1.

Description: In December 1997, the Society of Actuaries held a conference whose focus was actuarial and financial modeling. During the course of that conference, one of the speakers mentioned a number of technologies his firm was using for modeling, which were either unfamiliar or only vaguely familiar to some of the audience. The purpose of this paper is to define each of the technologies mentioned during that presentation and to briefly describe their distinguishing characteristics. The technologies discussed in this paper are statistical pattern recognition [SPR], neural networks [NNs], genetic algorithms [GAs], simulated annealing, fractal analysis, chaos theory, rule induction, data fusion algorithms [DFAs], data compression, fuzzy logic, case-based reasoning, and expert systems.

Description: A mathematical framework for benefits and choices must be created, in order to model flexible benefit selection. This paper creates such a framework by defining benefit plans as reimbursement functions. These are then used with a defined choice function to calculate the cost deviation due to selection. From Actuarial Research Clearing House 1992, VOL. 1.

Description: This research provides a literature review on the topic of post-retirement financial strategies from the perspective of an individual who is approaching retirement age. The body of knowledge surveyed is the post-retirement financial strategies literature that is related to the risks of longevity, inflation, and investment. The literature sources are both academic and practitioner-focused. The end product is a documentation of and commentary on the state-of-the-art in the post-retirement financial strategies area. The intended audience is retirement professionals, and others, who need to be well informed about the current state of post-retirement financial strategies, as reported in the literature.

Description: A fuzzy random variable [FRV] has been conceptualized as a vague perception of a crisp but unobservable random variable [RV] and also as a random fuzzy set. Since actuaries seem receptive to these notions of FRV, and there are sources of uncertainty that RVs can not accommodate, but FRVs can, one would expect FRVs to be a component of the actuarial arsenal, but generally this is not the case. Assuming that the reason for this is that potential users are not sufficiently familiar with FRV methodology, the purpose of this article is to help alleviate this situation by presenting a FRV primer.

Description: Genetic algorithms [GAs] and neural networks [NNs] are currently being used in actuarial and financial modeling. Nonetheless, while there is a general awareness of the nature of these techniques, there is often only vague familiarity with the details of how they are implemented. This paper is intended to help alleviate this situation. Its purpose is to present an overview of GAs and NNs, which includes an explanation of what they are, how they work, and an example of how they are implemented.

Description: A mathematical framework for benefits and choices must be created to model benefit selection. This paper creates such a framework by defining benefit plans as reimbursement functions. These are then used with a defined choice function to calculate the cost deviation due to selection. Finally, utility functions can be applied to this framework to predict choice.